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Moderate resolution imaging spectroradiometry (MODIS) snow cover accuracy has been assessed in the past at different scales, with various approaches and in relation to the many factors influencing the remote observation of snow-covered areas (SCA). However, the challenge of fully characterizing MODIS accuracy over forest sites is still open. In this study, we exploit 5 years of data from the upper river Adige basin at Ponte Adige (Eastern Italian Alps) to condition an enhanced temperature index snowpack model accounting for model parameter uncertainty by using the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. The simulated SCA is then compared with MODIS retrievals through a range of different statistical metrics to investigate how land use and solar illumination conditions affect such comparison. In particular, the Overall Accuracy index (OA) is used to quantify the agreement between satellite-derived and simulated SCA on a pixel-by-pixel basis. Analyzing the spatial variability either of the median OA and its range shows that illumination conditions over forested canopies represent a major source of uncertainty in MODIS SCA. Exploiting this finding, we identify the minimum level of incoming short-wave radiation for accurate use of MODIS SCA in forest areas.

Catchment geology has a major influence on the relative impact of the main seasonal hydrological predictability sources (initial conditions (IC), climate forcing (CF)) on the forecast skill as it defines the system’s persistence. A quantification of its effect, though, on the contribution of the predictability sources to the forecast skill has not been previously investigated. In this work we apply the End Point Blending (EPB) framework to assess the contribution of IC and CF to the seasonal streamflow forecast skill over two catchments that represent the end members of a set of catchments of contrasting geology, hence contrasting hydrological response: a highly-permeable, hence slow-responding catchment and a fast-responding catchment of low permeability. Our results show that the contribution of IC in the slow-responding catchment is higher by up to 44% for forecasts initialized in winter and spring and by up to 21% for forecasts initialized in summer. IC are important for up to 4 months of lead in the slow-responding catchment and 2 months of lead in the flashier catchment. Our analysis highlights the added value of the EPB in comparison to the traditional ESP/revESP approach for identifying the sources of seasonal hydrological predictability, on the basis of catchment geology.

<p>Seasonal hydrological forecasts are a powerful tool for water-related decision making associated to hydropower production, water supply and irrigation. The skill of these forecasts depends mainly on knowledge of the initial hydrologic conditions (ICs) on the start date of the forecast and knowledge of climate forcing (CF) during the forecast period. Identification of the sensitivity of the forecast skill to these two main predictability sources is crucial to funnel the efforts into improving the appropriate predictive tools, by either improving the ICs estimates or by enhancing the quality of the CF. This work aims at investigating the impact of catchment properties in terms of soil permeability on the contribution of the dominant predictability sources (ICs, CF) to the seasonal forecast skill. To this end, we apply the End Point Blending (EPB) framework to create forecasts with intermediate levels of uncertainty concerning ICs and CF. The methodology is applied in two catchments in the upper Adige River Basin that are representative of the two extremes of hydrological response: the Gadera catchment closed at Mantana (area: 390 km<sup>2</sup>, elevation range: 810–3050 m a.s.l.) that is highly permeable, hence slow-responding and the Passirio catchment closed at Merano (area: 402 km<sup>2</sup>, elevation range: 360–3500 m a.s.l.) that is characterized by low permeability, hence by a fast-responding regime. Our analysis highlights the contribution of each predictability source to the forecast skill over catchments of contradicting hydrological response, as well as the added value of the elasticity framework introduced by the EPB in comparison to the traditional ESP/revESP approach for identifying the sources of seasonal hydrological predictability in alpine areas.</p>